Pan-Cancer Analysis of Microfibrillar-Associated Protein 2 (MFAP2) Based on Bioinformatics and qPCR Verification

MFAP2 has been reported to play an oncogenic role in several types of human cancers. However, the expression profile of MFAP2 in various cancers and its impact on prognosis and immune infiltration remain unclear. In this study, the mRNA expression and protein expression of MFAP2 in normal tissues, tumor cell lines, and 33 malignant tumor tissues were analyzed comprehensively using Genotype-Tissue Expression (GTEx), Cancer Cell Line Encyclopedia (CCLE), and The Cancer Genome Atlas (TCGA), Oncomine and UALCAN databases, and the expression of MFAP2 in different grades and stages of cancers was assessed using Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Tumor and Immune System Interaction Database (TISIDB). In general, MFAP2 showed distinct expression in most tumor and normal tissues, closely associated with higher tumor grade, higher tumor stage, and poor survival in multiple cancers. A search of the UALCAN database and the cBioPortal database revealed that this difference in mRNA level expression could be partly attributed to abnormal DNA methylation and mutations at the genomic level. In addition, MFAP2 expression was also associated with tumor mutation burden, microsatellite instability, and neoantigens in different cancer types. More importantly, the TIMER and TISIDB databases also showed that MFAP2 levels were significantly correlated with immune infiltration abundance and immune-related gene markers, as well as ESTIMATE scores. By qPCR, MFAP2 expression was validated in four kinds of tumor tissue samples. The present study combined several databases and performed a pan-cancer analysis of the expression profile, methylation, and mutation for MFAP2 and its implications for prognosis and immune infiltration, suggesting that MFAP2 could contribute to malignant properties of many tumors. MFAP2 may be an important biomarker with prognostic value and has the potential to be a target for tumor immunotherapy.


Introduction
Immunotherapy is considered to be a promising treatment for cancers [1]. However, due to the heterogeneity of tumors, only 10-20% of the population can benefit from current immunotherapy [2,3]. For example, anti-CTLA4 has poor clinical efficacy in gastric cancer [4]. Anti-PD-1 and anti-PD-L1 have shown partial response in progressive colorectal cancer [5]. With the development of high-throughput sequencing technologies, abundant data are available to the public, such as TCGA database containing transcriptome data for 33 tumors. It is possible and necessary to perform pan-cancer analyses of genes and to assess their correlation with clinical prognosis and immune infiltration [6]. New biomarkers are urgently needed to predict prognosis and to find new immune-related therapeutic targets.
MFAP2 consists of a 183-amino-acid protein with 2 domains [7]. MFAP2 exists in two forms. One is extracellular MFAP2, which is a protein binding to fibrin, collagen VI, tropoelastin, deproteinized, and biglycan14. e other is intracellular protein, which is a functional protein upregulating downstream genes related to cell adhesion, movement, and matrix remodeling. In the last decade, aberrant expression of MFAP2 was found in various malignant tumors. MFAP2 is overexpressed in melanoma with its capacity of manipulating EMT-related proteins and Wnt/ β-catenin pathway to enhance melanoma invasion and migration ability [8]. Upregulation of MFAP2 in gastric carcinoma has been found, in which MFAP2 accelerates cancer cell migration via MFAP2/integrin α5β1/FAK/ERK pathway [9,10]. e ability of MFAP2 in activating TGFβ/SMAD2/3 pathway in gastric carcinoma has also been reported, and this activation accelerates the transformation of gastric carcinoma from an epithelial cell phenotype to a mesenchymal phenotype [11]. Previous studies have pointed out that MFAP2 possesses a hyperaffinity to TGF-β superfamily member in adipose tissue [12][13][14].
However, there are no pan-cancer studies on the relationship between MFAP2 and various cancers. Here, we retrieved multiple databases, GTEx, CCLE, Oncomine, TCGA, UALCAN, GEPIA2, and TISIDB, to analyze MFAP2 expression in pan-cancer and its relationship with prognosis. In addition, we explored the relationship between MFAP2 expression and gene mutations, promoter methylation, tumor neoantigens, tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) genes, and immune infiltration. Our results suggested that aberrant expression of MFAP2 was associated with its altered promoter methylation, affected immune infiltration in the tumor microenvironment, and also acted as a prognostic risk factor for a variety of cancers. is study was expected to provide a theoretical basis for gaining insight into the role of MFAP2 in tumor immunotherapy.

Gene Expression Analysis.
We downloaded the normalized pan-cancer datasets TCGA and GTEx from the UCSC database, extracted the expression data of MFAP2 gene in each sample, and further transformed each expression value as log2(x+1). e MFAP2 expression in 33 cancers was obtained. In addition, data of each tumor cell line were also downloaded from the CCLE database and analyzed the expression levels of MFAP2 in 21 tumor cell lines. Data analysis was performed using RStudio version 1.1.456 (RStudio Inc., USA) and the R package ggpubr. Moreover, the expression levels of MFAP2 gene in different cancers were identified in the Oncomine database [15], with the thresholds of p-value � 0.05, fold change � 2, and gene rank � ALL. MFAP2 protein expression was investigated in UALCAN database, providing us a platform for protein expression analysis of Clinical Proteomics Cancer Analysis Alliance dataset [16]. Finally, we explored MFAP2 expression in different pathological stages and grades of TCGA tumors via GEPIA2 and TISIDB databases.

Prognostic Analysis.
We first analyzed the relationship between MFAP2 expression in the 33 tumors and overall survival (OS) using TCGA data and visualized it with forest plots using univariate Cox regression analysis. Kaplan-Meier curves were further plotted to show the prognostic significance of MFAP2. Considering the possibility of non-tumor-related deaths during follow-up, we analyzed the relationship between MFAP2 expression and disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in the 33 TCGA tumors.

Genetic Changes Analysis.
On the website cBioPortal [17], we selected "TCGA Pan Cancer Atlas Studies" datasets. e mutations and copy number of MFAP2 were investigated, and MFAP2 mutation sites were displayed in schematic and 3D structure maps. e TMB and MSI scores of all samples were determined from the somatic mutation data downloaded from TCGA, and the correlation between MFAP2 expression and TMB and MSI was assessed using Spearman's rank correlation coefficient. e number of tumor neoantigens in each tumor sample was counted and its relationship with MFAP2 expression was analyzed. Moreover, TCGA expression profile data were used to analyze the expression of MMR genes, including MutL homologous gene (MLH1), MutS homologous gene (MSH2), MSH6, increased separation after meiosis (PMS2), and epithelial cell adhesion molecule (EPCAM) in different tumors. e correlation between MFAP2 and MMR genes was visualized in a heat map using the Reshape2 and R ColorBrewer packages.

DNA Methylation Analysis.
e UALCAN database was used to show the methylation levels of MFAP2 in different tumors and corresponding normal tissues. In addition, we analyzed the correlation between MFAP2 expression and the expression of the four methyltransferases, including DNMT1, DNMT2, DNMT3A, and DNMT3B.

Immune Infiltration Analysis.
We used TISIDB database, and TIMER, microenvironment cell populations (MCP)-counter and XCELL algorithms to explore the relationship between MFAP2 expression and immune infiltration in all TCGA tumors. We analyzed the stromal, immune, and ESTIMATE scores of each tumor sample using the ESTIMATE package and visualized the relationship between these scores and MFAP2 expression using scatter plots. In addition, we investigated the correlation of MFAP2 expression with monocyte and macrophage biomarkers using the TIMER database. Furthermore, we performed Spearman correlation analysis of MFAP2 and immune-related genes, including immunoinhibitors, immunostimulators, major histocompatibility complex (MHC) genes, chemokines, chemokine receptors, and immune checkpoints molecules. All data obtained were finally visualized in heat maps or scatter plots.
Hospital of Shandong province and conducted following the Declaration of Helsinki. (qPCR). Total RNA was extracted from tissues using TRIzol reagent (Invitrogen, ermo Fisher Scientific, Shanghai, China) and reverse-transcribed into cDNA using cDNA Reverse Transcription Kit (Applied Biosystems, Foster City, CA, USA). qPCR was performed using SYBR Premix Ex Taq II kit (RR820 A, TaKaRa, Dalian, China), with GAPDH as an internal reference. e relative expression of MFAP2 was calculated using the 2 −ΔΔCt method. e primers used are listed in Table 1.

Statistical Analysis.
e data were analyzed using R 4.0.2 software and GraphPad 9.0.0 and expressed as mean ± SD. Differences were analyzed by t-test, with p values less than 0.05 considered statistically significant.

MFAP2 Expression across Cancers.
We first examined the expression levels of MFAP2 in normal tissues via the GTEx dataset. As shown in Figure 1(a), MFAP2 expression levels were the highest in cervix uteri tissues and the lowest in blood and bone marrow tissues. Also, the basal levels of MFAP2 expression in various tumor cell lines were assessed. As shown in Figure 1(b), MFAP2 was expressed at the highest level in bone cell lines and the lowest level in haematopoietic and lymphoid cell lines.
To determine the differential expression of MFAP2, the Oncomine database was used to analyze MFAP2 mRNA levels in different tumors and corresponding normal tissues.
is analysis showed that, compared to normal tissues, MFAP2 expression was higher in bladder cancer, brain and central nervous system (CNS) cancer, breast cancer, colorectal cancer, esophageal cancer, gastric cancer, head and neck cancer, lymphoma, melanoma, myeloma, ovarian cancer, pancreatic cancer, and sarcoma. In some datasets of liver cancer and prostate cancer, no difference in expression was observed. In addition, MFAP2 expression was ambiguous in kidney cancer, leukemia, and lung cancer datasets; see Figure 2(a). Table 2 summarizes the details of MFAP2 expression in various cancers. To further assess the expression of MFAP2 in human cancers, we integrated transcriptomic data from all tumors in TCGA and GTEx. MFAP2 expression obtained from data in TCGA database and integrated data in the GTEx plus TCGA databases are shown in Figure 2(b) and Figure 2(c), respectively. Taking into account individual differences, we further assessed MFAP2 expression in paired samples Figure 2(d). e results showed that MFAP2 was significantly higher in BLCA, BRCA, CHOL, COAD, ESCA, HNSC, LIHC, LUAD, LUSC, READ, STAD, THCA, and UCEC than in adjacent normal tissues and significantly lower in KICH, KIRC, KIRP, and PRAD than in adjacent normal tissues. ere was no MFAP2 expression difference in PAAD, which may be due to the small sample size. Moreover, MFAP2 protein expression was elevated in breast cancer, colon cancer, and lung adenocarcinoma and reduced in clear cell renal cell carcinoma; see Figure 2(e).
Based on further analysis of the relationship between MFAP2 mRNA expression levels and cancer stage or grade, the results suggested that MFAP2 was positively correlated with the advanced BLCA stage in both GEPIA2 and TISIDB (see Figures 3(a) and 3(b)), and the TISIDB database of MFAP2 was positively correlated with the advanced CESC, KIRC, LGG, and LIHC grades (see Figure 3(c)).

MFAP2 Prognostic Value across Cancers.
To investigate the relationship between MFAP2 expression levels and prognosis in terms of DFI, DSS, OS, and PFI, we depicted forest plots for each cancer ( Figure 4). COX proportional risk model analysis showed that high expression of MFAP2 was associated with poor DFI for ACC, BRCA, CESC, CHOL, OV, and PAAD (Figure 4  e results showed that cholangiocarcinoma patients with deep deletion as the only mutation type had the highest frequency of MFAP2 alterations, exceeding 5%. In addition, amplification was the only type of MFAP2 mutation in the uterine carcinosarcoma samples, with a mutation frequency of over 3% ( Figure 5(a)). Figure 5(b) shows that between amino acids 0 and 183, a total of 29 MFAP2 mutation sites, including 27 missense and 2 splices, were detected, with missense being the predominant type of DNA alteration. Of these, F157 L in the ShKr protein domain was the most frequent mutant site, detected in 2 cases of endometrial carcinoma. Moreover, the MFAP2 mutant sites were further demonstrated in the 3D structure as shown in Figure 5(c). Additionally, we found that MFAP2 expression was independent of mutations ( Figure 5(d)) and independent of DNA copy variation Figure (5(e)).
MFAP2 expression in BLCA, BRCA, HNSC, and KICH tissues was shown by qPCR. e expression of MFAP2 was finally examined by qPCR in BLCA, BRCA, HNSC, and KICH tissue samples and the corresponding normal tissue samples. As a result, qPCR showed that MFAP2 expression was significantly lower in KICH tissues than in normal tissues, while it was significantly higher in the other three tumors (Figure 9).

Discussion
MFAP2 is an essential component of extracellular elastic microfibers, which interacts with and affects fibrin. It is also the constitutive protein of most vertebrate microfibrils [25]. A representative feature of MFAP2 is its capacity to work with TGF-β family growth factors, Notch, and Notch ligands, as well as a variety of elastins [26]. Mutations of MFAP2 gene may indicate thrombosis, thoracic aneurysms, metabolic diseases, and osteopenia in humans [27]. Studies have shown that MFAP2 is highly expressed in gastric cancer tissues, and its high expression is significantly related to the overall and disease-free survival of patients with gastric cancer [7]. Furthermore, MFAP2 is found to be a possible player in TGF-β/SMAD2/3 signaling pathway activation to advance proliferation, migration, invasion, and epithelialmesenchymal transition of gastric cancer cells [11]. A previous study pointed out that MFAP2 is a novel microRNA-29 target, and miR-29/MFAP2/integrinα5β1/FAK/ERK1/2 might be an important carcinogenic pathway in gastric cancer progression [10]. Another study has also indicated the relevance of MFAP2 in hepatic carcinoma, whereby MFAP2 overexpression in hepatic carcinoma is associated with cancer staging, poor OS, and disease-specific survival [9,26]. An in vitro experiment showed that downregulation of MFAP2 inhibited the proliferation and migration levels of liver cancer cells. Moreover, the transcription factors, DNA methyltransferases, and immune factors in liver cancer might interact with MFAP2 and accelerate tumor progression [27].
In this study, we found that MFAP2 exhibited different expression levels in different tissues and cells. e analysis based on Oncomine, TCGA, GTEx, and UALCAN databases revealed that MFAP2 mRNA and protein were aberrantly expressed in a variety of tumors. However, this aberrant expression was not associated with gene mutations and was influenced to some extent by its promoter methylation. Moreover, the expression of MFAP2 was significantly correlated with the pathological stage, grade, and prognosis of many cancers, suggesting that MFAP2 played an oncogene role in many tumors. In addition, MFAP2 expression was also correlated with DNA methyltransferases, TMB, MSI, and MMR-related genes. Aberrant DNA methylation is frequently seen during cancer progression [28]. MMR is an intracellular MMR mechanism, where the loss of function of key genes may lead to irreparable DNA replication errors and ultimately higher somatic mutations [29]. e correlation between MFAP2 and gene mutations further suggested its importance in tumorigenesis, although such mutations did not produce tumor neoantigens in most cancers.
Combining multiple algorithms, we found that MFAP2 was closely related to the immune infiltration profile in tumor tissue, affecting not only the proportion of immune cells but also the expression levels of many immune-related genes, including immune checkpoints. Among these, a type I transmembrane protein CD276 [30], recently identified as a promising target for tumor immunotherapy [31], is notable. Numerous studies have revealed that CD276 is overexpressed in a variety of tumors, including leukemia [32], breast cancer [33], prostate cancer [34], and other tumors, with expression levels strongly correlating with poor patient prognosis, and presumably involved in tumor immune evasion. In addition, CD276 has been shown to promote lactate production by promoting hexokinase 2 expression, thereby promoting glycolysis and drug resistance [35]. CD276 also could lead to increased NF-κB activity and elevated VEGF expression, further promoting tumor-associated angiogenesis and tumor invasion [36]. Despite unclear underlying mechanisms, the correlation between MFAP2 and CD276 in a variety of tumors suggests that MFAP2 is a promising target for tumor immunotherapy. In the next study, we intend to further verify the effect of MFAP2 on tumor cell proliferation, migration, and invasion and explore the molecular regulation mechanism.

Conclusion
In summary, our first pan-cancer analysis of MFAP2 suggested that MFAP2 could affect clinical prognosis in various cancers and immune cell infiltration, which deepened the understanding of the MFAP2 role in tumorigenesis. Data Availability e datasets used and/or analyzed during the current study are available from the corresponding author.

Conflicts of Interest
e authors declare that they have no competing interests.

Supplementary Materials
Supplementary Figure 1: correlation of MFAP2 expression with immune infiltration level in diverse kinds of cancers in TIMER database. Supplementary Figure 2: StromalScore (a), Immu-neScore (b), and ESTIMATEScore (c) were analyzed to estimate the correlation of MFAP2 expression with the proportion of immune and stroma in cancers. (Supplementary Materials)